Digital pathology: elementary, rapid and reliable automated image analysis

Histopathology. 2016 May;68(6):888-96. doi: 10.1111/his.12867. Epub 2015 Nov 25.


Aims: Slide digitalization has brought pathology to a new era, including powerful image analysis possibilities. However, while being a powerful prognostic tool, immunostaining automated analysis on digital images is still not implemented worldwide in routine clinical practice.

Methods and results: Digitalized biopsy sections from two independent cohorts of patients, immunostained for membrane or nuclear markers, were quantified with two automated methods. The first was based on stained cell counting through tissue segmentation, while the second relied upon stained area proportion within tissue sections. Different steps of image preparation, such as automated tissue detection, folds exclusion and scanning magnification, were also assessed and validated. Quantification of either stained cells or the stained area was found to be correlated highly for all tested markers. Both methods were also correlated with visual scoring performed by a pathologist. For an equivalent reliability, quantification of the stained area is, however, faster and easier to fine-tune and is therefore more compatible with time constraints for prognosis.

Conclusions: This work provides an incentive for the implementation of automated immunostaining analysis with a stained area method in routine laboratory practice.

Keywords: automation; biological markers; digital pathology; image analysis; immunohistochemistry; prognosis; reproducibility.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers, Tumor / analysis*
  • Carcinoma / diagnosis*
  • Carcinoma, Papillary
  • Carcinoma, Squamous Cell / diagnosis*
  • Head and Neck Neoplasms / diagnosis*
  • Humans
  • Image Interpretation, Computer-Assisted / methods*
  • Immunohistochemistry
  • Reproducibility of Results
  • Squamous Cell Carcinoma of Head and Neck
  • Thyroid Cancer, Papillary
  • Thyroid Neoplasms / diagnosis*


  • Biomarkers, Tumor